Philosophy of mind and cognitive science

Keywords: Bayes; Reinforcement Learning; Networks; Neuroeconomics; Dopamine; Neural simulations; Representations.

Colombo, M. (online first). Bayesian cognitive science, predictive brains, and the nativism debateSynthese.

Wright, C., Colombo, M., & Beard, A. (2017). HIT and Brain Reward Function: A Case of Mistaken Identity (Theory)History and Philosophy of Science Part CStudies in History and Philosophy of Biological and Biomedical Sciences. 64, 28-40.

Colombo, M., & Hartmann, S. (2017). Bayesian Cognitive Science, Unification, and ExplanationThe British Journal for Philosophy of Science, 68, 451-484.

Colombo, M. (2017). Social motivation in computational neuroscience. Or if brains are prediction machines, then the Humean theory of motivation is false. In J. Kiverstein (Ed.) Routledge Handbook of Philosophy of the Social Mind (pp. 320-340). New York: Routledge.

Colombo, M. & Wright, C.D. (2017). Explanatory Pluralism: An Unrewarding Prediction Error for Free Energy TheoristsBrain and Cognition, 112, 3-12.

Colombo, M. (2017). Why Build a Virtual Brain? Large-Scale Neural Simulations as Jump Start for Cognitive ComputingJournal of Experimental & Theoretical Artificial Intelligence, 29, 361-370.

Colombo, M. (2015). Why Build a Virtual Brain? Large-scale Neural Simulations as Test-bed for Artificial Computing Systems. In D.C. Noelle, R. Dale, A.S. Warlaumont, J. Yoshimi, T. Matlock, C.D. Jennings, & P.P. Maglio (Eds.), Proceedings of the 37th Annual Conference of the Cognitive Science Society (pp. 429-34). Austin, TX: Cognitive Science Society.

Colombo, M. (2015). For a Few Neurons More. Tractability and Neurally-Informed Economic ModellingThe British Journal for Philosophy of Science, 66, 713-736.

Colombo, M., & Sprenger, J. (2014). The Predictive Mind and Chess-Playing. A Reply to Shand (2014). Analysis, 74, 603-608.

Colombo, M. (2014). Neural Representationalism, the Hard Problem of Content, and Vitiated Verdicts. A Reply to Hutto & Myin (2013)Phenomenology and the Cognitive Sciences, 13, 257-274.

Colombo, M. (2014). Explaining Social Norm Compliance. A Plea for Neural RepresentationsPhenomenology and the Cognitive Sciences13: 217-138.

Colombo, M. (2014). Deep and Beautiful. The Reward Prediction Error Hypothesis of DopamineStudies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences, 45, 57-67.

Colombo, M. (2013). Moving Forward (and Beyond) the Modularity Debate. A Network PerspectivePhilosophy of Science, 80, 356-377.

Colombo, M., & Seriès, P. (2012). Bayes in the Brain. On Bayesian Modelling in NeuroscienceThe British Journal for Philosophy of Science, 63, 697-723.

Colombo, M. (2010). How ‘Authentic Intentionality’ can be enabled. A Neurocomputational HypothesisMinds and Machines, 20, 183-202.

Colombo, M. (2009). What Can Neuroscience Offer to Economics? Humana.Mente: Journal of Philosophical Studies, 10, 41-59.

Colombo, M. (2009). Does Embeddedness Tell Against Computationalism? A Tale of Bees and Sea Hares. AISB09 Proceedings of the 2nd Symposium on Computing and Philosophy, 16-21.

Colombo, M. (2008). No-Brainer Predictions. Predictive Models in the Ultimatum GameRerum Causae Journal of the LSE Philosophy Society, 1, 42-50.

Di Francesco, M., Motterlini, M., & Colombo, M. (2007). In search of the neurobiological basis of decision-making: Explanation, Reduction and EmergenceFunctional Neurology, 22, 197-204.

 

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